zhaoce_5545689.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "2824ffac",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "ba9d36d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerID</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Male</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Male</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Female</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Female</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Female</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   CustomerID  Gender  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0           1    Male   19                  15                      39\n",
       "1           2    Male   21                  15                      81\n",
       "2           3  Female   20                  16                       6\n",
       "3           4  Female   23                  16                      77\n",
       "4           5  Female   31                  17                      40"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('customers_segmentation.csv')\n",
    "data.head()\n",
    "#data.head()就是列出前五行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "b8ce5c6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "data.drop('CustomerID', axis = 1, inplace = True)\n",
    "#drop即是"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "7604d4c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Gender  Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0       1   19                  15                      39\n",
       "1       1   21                  15                      81\n",
       "2       0   20                  16                       6\n",
       "3       0   23                  16                      77\n",
       "4       0   31                  17                      40"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#编码，就变成数字容易计算\n",
    "encoder = LabelEncoder()\n",
    "#labelencoder()明显是一个函数，encoder是实例化了一个对象，所以下面encoder的用法才是encoder.xxxxx\n",
    "data['Gender'] = encoder.fit_transform(data['Gender'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "e8f32375",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#画图部分暂时跳过吧。。。\n",
    "## Bar chart to visualize the age distribution\n",
    "\n",
    "# Define the spending score range and its corresponding value\n",
    "ss1_20 = data[\"Spending Score (1-100)\"][(data[\"Spending Score (1-100)\"] >= 1) & (data[\"Spending Score (1-100)\"] <= 20)]\n",
    "ss21_40 = data[\"Spending Score (1-100)\"][(data[\"Spending Score (1-100)\"] >= 21) & (data[\"Spending Score (1-100)\"] <= 40)]\n",
    "ss41_60 = data[\"Spending Score (1-100)\"][(data[\"Spending Score (1-100)\"] >= 41) & (data[\"Spending Score (1-100)\"] <= 60)]\n",
    "ss61_80 = data[\"Spending Score (1-100)\"][(data[\"Spending Score (1-100)\"] >= 61) & (data[\"Spending Score (1-100)\"] <= 80)]\n",
    "ss81_100 = data[\"Spending Score (1-100)\"][(data[\"Spending Score (1-100)\"] >= 81) & (data[\"Spending Score (1-100)\"] <= 100)]\n",
    "\n",
    "# Define the X and Y axis label and value \n",
    "ssx = [\"1-20\", \"21-40\", \"41-60\", \"61-80\", \"81-100\"]\n",
    "ssy = [len(ss1_20.values), len(ss21_40.values), len(ss41_60.values), len(ss61_80.values), len(ss81_100.values)]\n",
    "\n",
    "# Plot the visualization\n",
    "plt.figure(figsize=(15,6)) # Define figure size\n",
    "sns.barplot(x=ssx, y=ssy, palette=\"nipy_spectral_r\") # Define the bar chart value\n",
    "plt.title(\"Spending Scores\") # Define bar chart title\n",
    "plt.xlabel(\"Score\") # Define bar chart X axis name \n",
    "plt.ylabel(\"Number of Customer Having the Score\") # Define bar chart Y axis name \n",
    "plt.show() # show plot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "4252c5ab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#3d图\n",
    "sns.set_style(\"white\")\n",
    "fig = plt.figure(figsize = (20, 10))\n",
    "ax = fig.add_subplot(111, projection= '3d')\n",
    "ax.scatter(data[\"Gender\"], data[\"Annual Income (k$)\"], data[\"Spending Score (1-100)\"], c = 'blue', s = 60)\n",
    "ax.view_init(30, 185)\n",
    "plt.xlabel(\"Gender\")\n",
    "plt.ylabel(\"Annual Income (k$)\")\n",
    "ax.set_zlabel('Spending Score (1-100)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "52bf03c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.128152</td>\n",
       "      <td>-1.424569</td>\n",
       "      <td>-1.738999</td>\n",
       "      <td>-0.434801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.128152</td>\n",
       "      <td>-1.281035</td>\n",
       "      <td>-1.738999</td>\n",
       "      <td>1.195704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.886405</td>\n",
       "      <td>-1.352802</td>\n",
       "      <td>-1.700830</td>\n",
       "      <td>-1.715913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.886405</td>\n",
       "      <td>-1.137502</td>\n",
       "      <td>-1.700830</td>\n",
       "      <td>1.040418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.886405</td>\n",
       "      <td>-0.563369</td>\n",
       "      <td>-1.662660</td>\n",
       "      <td>-0.395980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>-0.886405</td>\n",
       "      <td>-0.276302</td>\n",
       "      <td>2.268791</td>\n",
       "      <td>1.118061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>-0.886405</td>\n",
       "      <td>0.441365</td>\n",
       "      <td>2.497807</td>\n",
       "      <td>-0.861839</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>1.128152</td>\n",
       "      <td>-0.491602</td>\n",
       "      <td>2.497807</td>\n",
       "      <td>0.923953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>1.128152</td>\n",
       "      <td>-0.491602</td>\n",
       "      <td>2.917671</td>\n",
       "      <td>-1.250054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>1.128152</td>\n",
       "      <td>-0.635135</td>\n",
       "      <td>2.917671</td>\n",
       "      <td>1.273347</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>200 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Gender       Age  Annual Income (k$)  Spending Score (1-100)\n",
       "0    1.128152 -1.424569           -1.738999               -0.434801\n",
       "1    1.128152 -1.281035           -1.738999                1.195704\n",
       "2   -0.886405 -1.352802           -1.700830               -1.715913\n",
       "3   -0.886405 -1.137502           -1.700830                1.040418\n",
       "4   -0.886405 -0.563369           -1.662660               -0.395980\n",
       "..        ...       ...                 ...                     ...\n",
       "195 -0.886405 -0.276302            2.268791                1.118061\n",
       "196 -0.886405  0.441365            2.497807               -0.861839\n",
       "197  1.128152 -0.491602            2.497807                0.923953\n",
       "198  1.128152 -0.491602            2.917671               -1.250054\n",
       "199  1.128152 -0.635135            2.917671                1.273347\n",
       "\n",
       "[200 rows x 4 columns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler = StandardScaler()\n",
    "#一样，实例化\n",
    "scaled_data = pd.DataFrame(scaler.fit_transform(data), columns = data.columns)\n",
    "scaled_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "e1de8038",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\sklearn\\cluster\\_kmeans.py:881: UserWarning: KMeans is known to have a memory leak on Windows with MKL, when there are less chunks than available threads. You can avoid it by setting the environment variable OMP_NUM_THREADS=1.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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ICHr16kVRURHjx4+v7MdxTVOnwgcfQGYmzJoFI0aYXZGIiIhIjVLpIXzcuHGMGzfuvPaUlJTz2mJjY4mNjbVr8/X1Zfbs2efd27JlS1JTU89rT0hIICEh4TIqlvMEBhqH+ERHw/jx0K0bNG5sdlUiIiIiNYYO65HSde4MffrA6dPwxBNgs5ldkYiIiEiNoRAuZZs1C0JC4N//hjfeMLsaERERkRpDIVzKFhICZ6cGPfMMHDhgbj0iIiIiNYRCuFxY795w//1w/DgMGWJ2NSIiIiI1gkK4XJjFAvPmGYs133sPVqwwuyIRERGRak8hXMpXvz688ILxesgQ+O03c+sRERERqeYUwqViBg6EyEj49VftGy4iIiJymRTCpWLc3GDBAvDyMnZKWbfO7IpEREREqi2FcKm4pk2Nw3vA2Dv81Clz6xERERGppioUwjMyMkhNTWXnzp3k5eVVdU3izP7+dwgPhx9/LAnkIiIiInJRyg3hiYmJvP/++7z77rtkZ2czZswYR9QlzsrTExYuNKanvPwyfPml2RWJiIiIVDvlhvDMzExefPFF/Pz86NatG7/88osj6hJnFhEBw4dDURE8/jgUFJhdkYiIiEi1Um4ILywsJC8vD4vFQmFhIW5umkYuwD/+AY0awfbt8OKLZlcjIiIiUq2Um6gfffRRunfvzvfff0/Pnj3p06ePI+oSZ+fnZ+yWAkYg37nT3HpEREREqhGP8m4IDg5myZIl7N69m9DQUGrXru2IuqQ6uPtu6N/fmCM+YABs2GDMFRcRERGRCyo3Mc2ZM4crrriC8PBwBXA530svwTXXQHo6zJ9vdjUiIiIi1UK5I+EWi4XBgwfTsGHD4vngTz/9dJUXJtVErVrw6qvQoweMGgVdukBYmNlViYiIiDi1ckN4jx49HFGHVGfduxvXe+/BoEGwejVYLGZXJSIiIuK0yp2O8sADD9CgQQNCQ0OpV68enp6ejqhLqpu5cyE4GNauhaVLza5GRERExKmVOxI+ZMgQCgoKOHToEIWFhVx11VV06dLFEbVJdXLttTBjhrFv+FNPwb33QkiI2VWJiIiIOKVyR8KtVisLFy4kPDyc9957T8fWS9n69TN2TDlyBIYNM7saEREREadVbgj38DAGy0+fPo2Pjw8FOh1RymKxwOuvg68vvPMOfPih2RWJiIiIOKVyQ3jHjh2ZO3cuTZs2JTY2loCAAEfUJdVV48YwebLx+m9/g5wcc+sRERERcULlzgk/94TMv/71rzRo0KAq65Ga4KmnICUFvvoKxo6FOXPMrkhERETEqZQbwseMGXNe27Rp06qkGKkhPDyMUzTbtDH2EI+LgzvvNLsqEREREadRbgiPjo4GwGazsWPHDg4dOlTlRUkNEB5uHN4zZYpxtP3WreDjY3ZVIiIiIk6h3Dnh7dq1o127drRv356BAwfy888/O6AsqRHGjYMbboCdO40wLiIiIiJABUbC09PTi18fPnyYI0eOVGlBUoP4+MA//wnt2sELL0DPnsYIuYiIiIiLKzeEr1mzpvi1l5cXU6dOrdKCpIaJjIQnn4SkJOMgn4wMcHc3uyoRERERU5UbwrUIUy7btGmwahV8+SW88go8/bTZFYmIiIiYqtwQ3qlTJw4cOEC9evX49ddf8fT0xMvLC7CfqiJSpqAgmD8funQx5ol37QqNGpldlYiIiIhpyl2YeeONN7J27Vo+/PBDPv30U+68807S09MVwOXi3H+/sVXh6dPGIT42m9kViYiIiJim3BC+b98+QkNDAQgJCeHgwYNVXpTUUK+8AldeCZ99Bt7eNGve3DjiPi3N7MpEREREHKrcEN6wYUNGjBhBcnIyw4YNo2XLlg4oS2qkOnWMUXCAggLjz9xcY5qKgriIiIi4kHLnhE+ZMoWPP/6Yffv20aNHD9q1a+eIuqSmSkw8v+3UKYiONqaqiIiIiLiAC46Ef/bZZ7i5uREZGcnRo0f56quvOHXqlKNqk5ooN/fi2kVERERqoDJD+IwZM/jggw84c+YMkydP5tSpU9SqVYuJEyc6sDypcco6ul5H2ouIiIgLKXM6SlZWFosWLeLMmTOsX7+eDRs24OvrS1xcnCPrk5pm7VpjDvif/0XluefMqUdERETEBGWOhLv/carh9u3badKkCb6+vgAUnF1QJ3IpoqJg9eqSkW+PP/4e+PzzsHmzeXWJiIiIONAFQ3h6ejrvvPMO9957LwBffPEFQUFBDitOaqioKDh9muwdOyA/H/r1MxZldukC331ndnUiIiIiVa7MEP7ss8+yfPlyrrnmGuLi4vj888954YUXGDdunCPrk5rOYjFO04yOhiNH4L77QHvRi4iISA1X5pzwsLAwZs2aVfx1u3bt7LYnTElJoXfv3lVanLgIT09ITTVGyL/80gjk69dDYKDZlYmIiIhUiXIP6ynL2rVrK7MOcXX+/sZc8caN4euvoWfPkgN9RERERGqYSw7hNputMusQgauugo8+Mk7W/PhjGDAA9HsmIiIiNdAlh3CLxVKZdYgY/vIXWLMG/Pzgrbe0daGIiIjUSJccwkWqzC23wLJl4O4OU6bAvHlmVyQiIiJSqcoM4Tk5ORf8wbKmoxQUFDBy5Eji4+OJiYlh3bp17N69m7i4OOLj45kwYQJFRUUApKam0r17d2JjY0lLSwMgNzeXhIQE4uPjGTBgAMeOHQNg27Zt9OzZk969ezN37tziz5s7dy4xMTH07t2b7du3X9zTi/OKjobXXzdeDxkCK1eaWo6IiIhIZSozhA8cOBCACRMmlPr9kSNHltq+atUqgoODWbJkCQsWLGDy5MlMmzaNYcOGsWTJEmw2G+vWrePw4cMkJyeTkpLCwoULSUxMJD8/n6VLl9KkSROWLFlC165dSUpKKq5j5syZLF26lG+++YasrCyysrLYsmULy5YtIzExkUmTJl1uf4gz6dcP/vEPKCqCuDj44guzKxIRERGpFGVuUejj40OPHj3YvXs3//vf/wBj9NtisZCSkkJ4eHipP3fffffRqVOn4q/d3d3Jysri1ltvBaB9+/Zs2rQJNzc3WrVqhZeXF15eXoSFhbFz504yMzN5/PHHi+9NSkrCarWSn59PWFgYAJGRkWRkZODl5UVkZCQWi4W6detSWFjIsWPHqF27duX0jphv3Dj45RdjVPyBB2DTJmja1OyqRERERC5LmSF8wYIFHDp0iPHjxzNx4sQK74bi7+8PgNVqZejQoQwbNozp06cXL+T09/cnJycHq9VK4Dn7QPv7+2O1Wu3az703ICDA7t69e/fi7e1NcHCwXXtOTk65ITw/P5/s7OwKPU9lys3NNeVznVWF+2PIEEK//57AtDTy77mH3UuXcqZOnaov0MH0+1FCfWFP/WFP/VFCfWFP/VFCfWHPGfujzBDu5ubGNddcQ1JSEu+++y4//PADDRo0IC4urtw3PXDgAIMHDyY+Pp4HHniAl156qfh7J0+eJCgoiICAAE6ePGnXHhgYaNd+oXuDgoLw9PQs9T3K4+XlRbNmzcq9r7JlZ2eb8rnO6qL6Y/VquPtuvDZv5vqnnoINGyAoqGoLdDD9fpRQX9hTf9hTf5RQX9hTf5RQX9hzxv4od3eU8ePHs2fPHtq2bcu+ffvKPbb+yJEj9OvXj5EjRxITEwNA8+bN2bx5MwAbN24kIiKC8PBwMjMzycvLIycnh127dtGkSRNat27Nhg0biu9t06YNAQEBeHp6smfPHmw2G+np6URERNC6dWvS09MpKipi//79FBUVaSpKTeXnZwTx66+HbdugRw/Izze7KhEREZFLUuZI+Fm7d+/mnXfeAaBDhw7lHlU/f/58Tpw4QVJSUvGiymeffZbnn3+exMREGjVqRKdOnXB3d6dv377Ex8djs9kYPnw43t7exMXFMWrUKOLi4vD09GTmzJkATJo0iREjRlBYWEhkZCQ333wzABEREfTq1YuioiLGjx9/WZ0hTi4kxDjM58474bPPjIWbb78NbtppU0RERKqXckN4Xl4ep0+fxtfXl9zcXAoLCy94/7hx40odLV+8ePF5bbGxscTGxtq1+fr6Mnv27PPubdmyJampqee1JyQkkJCQUN5jSE3RqBGsXQt//Su88w6EhsILL5hdlYiIiMhFKTeEP/LIIzz00ENcf/31/PDDDwwdOtQRdYmUrXVrWLEC7r8fpk+HevVAfxETERGRaqTcEP7ggw/Svn179u7dS2hoKLVq1QLgs88+o0OHDlVeoEip7r0XFi6E//s/eOopqFvXmCcuIiIiUg1UaDJtcHAwN910U3EAB3j77berrCiRCnnkEZg6FWw26NMHPv/c7IpEREREKuSSV7RVdN9wkSo1ejQ8+STk5cGDD8KOHWZXJCIiIlKuSw7hZw/fETGVxQKzZ0PXrvD773DffbBvn9lViYiIiFyQ9naT6s/dHZYsMbYu3LsXOneG48fNrkpERESkTJqOIjWDry+sWgVNm8K330K3bsYUFREREREnVKEQbrVaOXr0aPEF8Nhjj1VpYSIX7corjcN8rr0W0tLg0UehqMjsqkRERETOU+4WhX//+9/JzMwkKCgIm82GxWLh/fff5+6773ZEfSIX57rrjMN82reHlBRjD/EZM8yuSkRERMROuSH8p59+Yt26dY6oRaRytGwJ779vzA2fOdMI4sOHm12ViIiISLFyp6OEh4fz448/OqIWkcpzzz2waJHx+umn4d13za1HRERE5BzljoQHBAQQExODn59fcVt6enqVFiVSKfr0gf374e9/Nw72ufpquOsus6sSERERKT+Eb968mS1btuDhUe6tIs5nxAj45ZeSvcQ//xxuusnsqkRERMTFlTsdpUGDBsU7oohUOxYLJCZCjx7G3uGdOxt7iYuIiIiYqNzh7czMTO6++25q1apV3KbpKFKtuLvD4sVw6JAxEt65s/HnOb/TIiIiIo5Ubgj/9NNPHVGHSNXy8YEPPoDISMjKMqamfPyx0S4iIiLiYOWG8DFjxpzXNm3atCopRqRK1aoFH34Id9wBGzdC377Grilul3xwrIiIiMglKTeER0dHA8Yx9Tt27ODQoUNVXpRIlQkLM4J4u3awfLmxf/isWcbccREREREHKTeEt2vXrvh1+/bt6devX5UWJFLlwsNh5Uro1MnYNaV+fWMXFREREREHKTeEn7sI8/Dhwxw5cqRKCxJxiKgoePttiIuDkSOhbl2Ijze7KhEREXER5YbwNWvWFL/28vJi6tSpVVqQiMP07m0c5vPMM/Doo8ZhPvfcY3ZVIiIi4gLKDeFnF2F+//33eHp60qBBg6quScRxnn7aOMzn5ZehWzdj68Kbbza7KhEREanhytwWYtOmTdx1110UFBSQkpLCoEGD+Pvf/86yZcscWZ9I1ZsxA2JjISfH2EN8926zKxIREZEarswQvnDhQlJTU/H09OT1119n4cKFLF68mOXLlzuyPpGq5+ZmzA+/6y44cADuuw+OHTO7KhEREanBygzhFouFq666ir179+Lp6cl1112Hl5cX7u7ujqxPxDG8veH99+HGG2HnTnjwQTh92uyqREREpIYqM4SfOXOGM2fOsH79eiIjIwE4ceIEpxVMpKYKDjb2EA8NhU2boE8fKCw0uyoRERGpgcoM4d26dSM6Opo333yTRx99lO+++46HH36YPn36OLI+EccKDYWPPjIC+fvvw9ChYLOZXZWIiIjUMGXujtK1a1c6dOiAn58fbm5uHDp0iBdeeIHmzZsDsG/fPurVq+ewQkUcpkUL+OAD6NgRkpKMw3xGjza7KhEREalByhwJBwgICMDNzbjlqquuKg7gAGPGjKnaykTM1L49LF5sHGc/ZoyxcFNERESkklwwhF+ITf9ELzVdz54wa5bxun9/+OQTU8sRERGRmuOSQ7jFYqnMOkSc09ChxrH2Z85Ajx7w9ddmVyQiIiI1wCWHcBGX8cILEB8PVitER8NPP5ldkYiIiFRzmo4iUh43N1i0CO65Bw4eNA7zOXLE7KpERESkGis3hK9atarU9ttvv73SixFxWl5e8N57cPPN8N138MADcOqU2VWJiIhINVVuCE9NTS21ffDgwZVejIhTCwqCtWshLAz+8x+IizPmiouIiIhcpDL3CT8rPz+frl270rBhw+LtCmfOnFnlhYk4pbp1jcN82raFVatg8GCYP9/YylBERESkgsoN4SNGjHBEHSLVR7Nm8K9/QYcO8PrrxmE+48aZXZWIiIhUI+VOR2nevDmbNm1i5cqV/P7771x99dWOqEvEubVtC0uWGCPgzz1nLNwUERERqaByQ/jYsWOpX78+P//8MyEhITz77LOOqEvE+XXrBnPmGK8HDIAPPzS3HhEREak2yg3hv//+OzExMXh4eNC6dWttTShyrsGDjWPtCwshJga+/NLsikRERKQaqNA+4bt27QLg119/LV6cKSJ/mDIFHnnE2LLw/vvhj/9eRERERMpSbqIeN24cY8eOZceOHQwdOpQxY8Y4oi6R6sNigX/+E+69Fw4fhk6d4NAhs6sSERERJ1ZuCN+3bx/vvvsuX331Fampqfz8888OKEukmvH0hOXLoVUrYyS8Sxc4edLsqkRERMRJlblFYVpaGl9//TVr1qxh69atABQVFbFu3Tqio6MdVqBItREYaBzmc8cdxtzw2Fj44APwKHcnUBEREXExZaaDpk2b8vvvv+Pt7U3Dhg0BsFgs3H///Q4rTqTaueaaksN81q6FgQNhwQId5iMiIiJ2ygzh1157Ld26deOhhx4CjFHwbdu20bhxY4cVJ1It3XADrF4Nd98NCxdCaChMnGh2VSIiIuJEyv138pkzZ1K/fn32799PVlYWISEhTJ8+3RG1iVRft98OKSnGXuKTJkG9esZe4iIiIiJUYGFmZmYmvXv3ZuvWrSxcuJBff/21Qm/8zTff0LdvXwCysrJo164dffv2pW/fvqxduxaA1NRUunfvTmxsLGlpaQDk5uaSkJBAfHw8AwYM4NixYwBs27aNnj170rt3b+bOnVv8OXPnziUmJobevXuzffv2i3t6kar04IOQlGS8HjjQGB0XERERoQIj4UVFRWzfvp3Q0FDy8/OLQ/GFLFiwgFWrVuHr6wvAjh07eOyxx+jXr1/xPYcPHyY5OZkVK1aQl5dHfHw8bdu2ZenSpTRp0oSEhATWrFlDUlIS48aNY8KECcyZM4f69evzxBNPkJWVBcCWLVtYtmwZBw4cICEhgRUrVlxqX4hUvr/9Dfbtg8mTjYWaaWlw221mVyUiIiImK3ck/KGHHmLy5Mn069ePl156iUceeaTcNw0LC2PO2eO8gf/+97+sX7+ePn36MHbsWKxWK9u3b6dVq1Z4eXkRGBhIWFgYO3fuJDMzk3bt2gHQvn17MjIysFqt5OfnExYWhsViITIykoyMDDIzM4mMjMRisVC3bl0KCwsr9JcEEYeaNAkeewxOnza2LvzuO7MrEhEREZOVOxLep08f+vTpA8Czzz5boTft1KkTv/zyS/HX4eHh9OzZkxtvvJF58+bx6quv0rRpUwIDA4vv8ff3x2q1YrVai9v9/f3JycnBarUSEBBgd+/evXvx9vYmODjYrj0nJ4fatWtfsL78/Hyys7Mr9CyVKTc315TPdVYu1R/DhlH/hx8I+Pxz8u+5h5+XLKEwJMTuFpfqj3KoL+ypP+ypP0qoL+ypP0qoL+w5Y3+UG8LvvvtuLOdsrxYQEMAHH3xwUR/SsWNHgoKCil9PnjyZiIgITp5zmMnJkycJDAwkICCguP3kyZMEBQXZtZ3b7unpWep7lMfLy4tmzZpd1DNUhuzsbFM+11m5XH+sXQtRUXh99RVNhg2D9euNvcX/4HL9cQHqC3vqD3vqjxLqC3vqjxLqC3vO2B/lTkf56KOP+PDDD1m7di0vvvgit95660V/SP/+/YsXTWZkZNCiRQvCw8PJzMwkLy+PnJwcdu3aRZMmTWjdujUbNmwAYOPGjbRp04aAgAA8PT3Zs2cPNpuN9PR0IiIiaN26Nenp6RQVFbF//36KiorKHQUXMU1AAKxZA40bw9dfQ8+eUFBgdlUiIiJignJHwr28vIpft2nThsTExIv+kIkTJzJ58mQ8PT0JCQlh8uTJBAQE0LdvX+Lj47HZbAwfPhxvb2/i4uIYNWoUcXFxeHp6MnPmTAAmTZrEiBEjKCwsJDIykptvvhmAiIgIevXqRVFREePHj7/o2kQc6qqrjMN87rwTPv7Y2LZw0SId5iMiIuJiKrRP+NnpKIcOHcLNrdzBcwBCQ0NJTU0FoEWLFqSkpJx3T2xsLLGxsXZtvr6+zJ49+7x7W7ZsWfx+50pISCAhIaFCNYk4hb/8xdiuMCoK3noLzpyBFStolpsLPj7F01ZERESk5io3hDdq1Kj4ddOmTYt3LhGRy3DrrZCaauwl/s47Je25ucYOKmdDuoiIiNRIZYbw9PR0AOrUqWPX/s033xAZGVm1VYm4gvvvB3d3KCqybz91CqKjjS0NRUREpEYqM4SvWbOmzB9SCBepJGUtzMzNdWwdIiIi4lBlhvBp06bx+++/F+/DfeTIEdzc3LT7iEhl8vEpPXB7eEB+PpyzMFpERERqjjJXWW7ZsoVu3bpx/PhxAP73v//Ro0cPvvrqK4cVJ1LjrV0Lfn7nt585A61bwxdfOL4mERERqXJlhvBZs2aRnJzMFVdcAUDbtm154403LmmLQhEpQ1SUsQjTx8f42scHZswwdlDJyoK2bWHQIPj9d1PLFBERkcpVZgh3d3cnNDTUrq1hw4YV3qJQRCooKgpOnyZ7xw5jMeYzz8D27TB2rDEtZf58aNYMli0Dm83sakVERKQSlJmobTYbRX/ataGwsJACnfAnUvV8fWHKFNi6Fe64A379FWJjjS0N9+wxuzoRERG5TGWG8AcffJCnn36anTt3YrVa+eGHHxg5ciSdO3d2ZH0iru3GGyE9HebNg6AgY+pK8+bw8svGvHERERGplsrcHSU2NpaAgACmTp3KoUOHqFevHj169CA6OtqR9YmImxsMHGiMgj/1FCxfDk8/DYsXw4IFxgJOERERqVYueGJmdHR0maF77ty5DBkypEqKEpFS1K1rzAtfvRqefBK+/hpuuQWGDYNJkyAgwOwKRUREpIIueZXlli1bKrMOEamoLl1gxw4YPtz4OjERWrSACxywJSIiIs7lkkO4Tbs0iJgnIMAI31u2QKtWxmLNLl2MxZsHDphdnYiIiJTjkkO4xWKpzDpE5FK0aWME8ZkzjUN/li0ztjN87TX40+5GIiIi4jy06bdIdefhYSzUzMqC6Gg4ftxYyNm+vdEmIiIiTkfTUURqigYNjEWb774LV18NmzYZU1Weew5yc82uTkRERM5Rbgi32Wxs376dL7/8svgCePHFF6u8OBG5SBaLMS98507429+goACefx7Cw+Hf/za7OhEREfnDBbcoBEhISODo0aNce+21gDEX/JZbbin+WkScUHCwcdz9ww8bYXzHDrjnHvi//4MZMyAkxOwKRUREXFq5IfzIkSOkpKQ4ohYRqWyRkbB1K7z4ojEi/tZbxlaGiYlGQNcCaxEREVOUOx2lYcOGHDx40BG1iEhV8PKCceNg+3aIioIjR+CRR6BjR/jhB7OrExERcUnlhvDMzEyioqKIjIwsvkSkGmrSBNatg0WLoHZt4/VNN8HUqZCfb3Z1IiIiLqXc6SiffPKJI+oQEUewWODRR+H+++GZZyA5GZ59FpYuhddfhzvuMLtCERERl1BmCE9KSuLJJ5/k6aefPu9gnpkzZ1Z5YSJSherUgbffNqalDBwI//0vtG1rvJ42Da64wuwKRUREarQyQ/jdd98NQO/evR1WjIg4WIcO8O23xqLNF1+EefNg5UqYMwe6d9fCTRERkSpS5pzwpk2bAlC3bl2+/fZbtmzZUnyJSA3i6wtTpsDXXxvTUQ4cgJgYeOgh2LPH7OpERERqpHIXZj7zzDOcPn2akJCQ4ktEaqCbboL0dEhKgqAg+Ne/oHlzmDULCgvNrk5ERKRGKXdhpo+PD0OGDHFELSJiNjc3GDTIGAUfOhRWrIDhw2HxYliwAFq1MrtCERGRGqHMkfCffvqJn376iZCQEFavXs2PP/5Y3CYiNVzdurB8OaxaBfXrQ2YmRETAiBFw8qTZ1YmIiFR7ZY6Ejx8/vvj1u+++W/zaYrHw9ttvV21VIuIcHngA7roLxo+H2bNh5kwjnCclQXS02dWJiIhUW2WG8OTkZADS0tKIiooqbl+7dm3VVyUiziMwEF5+Gfr0gQEDYNs2Y5/x2Fh45RW45hqzKxQREal2ygzhaWlpbN26ldWrV7N161YAioqKWLduHdEaARNxPRER8OWXRvAePx5SU+GTT2D6dHj8cWM+uYiIiFTIBbcobNiwId7e3jRs2JCGDRvyl7/8hcTEREfWJyLOxMPDOGkzKws6d4bff4e//Q3at4cdO8yuTkREpNoocyS8Tp06dOvWjc6dO+OmES4ROVeDBrBmjTEa/tRTsGkTtGwJo0bBs8+Cj4/ZFYqIiDi1MtP18OHDAYiOjqZz58507tyZ++67j86dOzusOBFxYhYL9OoF2dnwxBNQUGCcvBkeDmlpZlcnIiLi1MocCf/tt9/o2LEjt912G+3ataNt27ZcccUVjqxNRKqDWrXgtdegb18jjGdnw913w6OPwowZcOWVZlcoIiLidMocCV+8eDFr1qyha9eu7Nq1i2HDhvHYY4+RlJTkyPpEpLqIjIStW+Ef/wBvb3jzTWja1Djox2YzuzoRERGncsHJ3l5eXrRo0YIbbriBG264gTNnzrBDi69EpCze3vDcc7B9u7G/+JEjxgh5p06wa5fZ1YmIiDiNMqejLFq0iPXr15OTk8Mdd9zBXXfdxTPPPIOnp6cj6xOR6qhJE/j3v+Gtt4zdVD79FG680djacMQI0P9HRETExZU5Ev7qq69Su3ZtRowYwbBhw7j99tsVwEWk4iwWY174zp3GaHhuLowdC23awH/+Y3Z1IiIipiozhGdkZBAbG8vnn39OXFwcgwYNYunSpezfv9+R9YlIdVenDrz9tnGwT+PG8O23cOedMHgwHD9udnUiIiKmKDOEe3p6cscddzBq1CiWL19OXFwcq1ev5p577nFkfSJSU3TsaATwMWPA3R2SkqB5c1ixQgs3RUTE5ZQZwr/99lvefPNNhgwZQnR0NCtXrqRr166sW7fOkfWJSE3i6wtTp8LXX8Ptt8P+/RATA127wt69ZlcnIiLiMGUuzJwxYwaRkZEMGjSI5s2bY7FYHFmXiNRkN91knLI5f74xMr5qlbGQ8//+DxYupFlurnHq5tq1EBVldrUiIiKVrswQ/tZbbzmyDhFxNW5u8OSTxij40KHGtJRXXy35fm4udOkCq1criIuISI1zwX3CRUSqXN26sHx56dsWnjoF0dGOr0lERKSKKYSLiHMoKCi9PTcX1q3T4k0REalRFMJFxDn4+JT9vQ4d4JZbjBHzwkLH1SQiIlJFqiyEf/PNN/Tt2xeA3bt3ExcXR3x8PBMmTKCoqAiA1NRUunfvTmxsLGlpaQDk5uaSkJBAfHw8AwYM4NixYwBs27aNnj170rt3b+bOnVv8OXPnziUmJobevXuzffv2qnocEalqa9eCn599m68v9Otn7DWemQk9e0KzZvD668YIuYiISDVVJSF8wYIFjBs3jry8PACmTZvGsGHDWLJkCTabjXXr1nH48GGSk5NJSUlh4cKFJCYmkp+fz9KlS2nSpAlLliyha9euJCUlATBhwgRmzpzJ0qVL+eabb8jKyiIrK4stW7awbNkyEhMTmTRpUlU8jog4QlSUsQjz7Ii4jw+sWQMLF8Lu3caizYYN4fvv4W9/M16/+KIO/BERkWqpSkJ4WFgYc+bMKf46KyuLW2+9FYD27dvzxRdfsH37dlq1aoWXlxeBgYGEhYWxc+dOMjMzadeuXfG9GRkZWK1W8vPzCQsLw2KxEBkZSUZGBpmZmURGRmKxWKhbty6FhYXFI+ciUg1FRcHp02Tv2AGnT5fsiuLra+yk8t13sHQp3Hwz/PorjBoFYWEwerTxtYiISDVR5haFl6NTp0788ssvxV/bbLbifcb9/f3JycnBarUSGBhYfI+/vz9Wq9Wu/dx7AwIC7O7du3cv3t7eBAcH27Xn5ORQu3btC9aXn59PdnZ2ZTzqRcnNzTXlc52V+sOe+qPEBfvi5pthyRL809O5cuFC/LdsgenTKXr5ZY4/9BBH+/Wj4LrrHFtwFdPvhj31Rwn1hT31Rwn1hT1n7I8qCeF/5uZWMuB+8uRJgoKCCAgI4OTJk3btgYGBdu0XujcoKAhPT89S36M8Xl5eNGvWrDIe7aJkZ2eb8rnOSv1hT/1RokJ90bw5PPEEbN4M06fjtnIltZYto9aKFdCjhzFK3qaNYwquYvrdsKf+KKG+sKf+KKG+sOeM/eGQ3VGaN2/O5s2bAdi4cSMRERGEh4eTmZlJXl4eOTk57Nq1iyZNmtC6dWs2bNhQfG+bNm0ICAjA09OTPXv2YLPZSE9PJyIigtatW5Oenk5RURH79++nqKio3FFwEalhbrsN3nsPduwwFnG6u8OyZRARAR07antDERFxSg4ZCR81ahTPPfcciYmJNGrUiE6dOuHu7k7fvn2Jj4/HZrMxfPhwvL29iYuLY9SoUcTFxeHp6cnMmTMBmDRpEiNGjKCwsJDIyEhuvvlmACIiIujVqxdFRUWMHz/eEY8jIs6oaVNjEec//gEvvwyvvQaffWZcbdoY88a7dTNCuoiIiMmqLISHhoaSmpoKQMOGDVm8ePF598TGxhIbG2vX5uvry+zZs8+7t2XLlsXvd66EhAQSEhIqqWoRqfbq1YMZM+DZZyEpCV55pWR7w+uvhxEj4JFHLrwvuYiISBXTYT0iUjPVqmUEcW1vKCIiTkghXERqNm1vKCIiTkghXERcg4cH9O4NW7fChx/CXXfBiRMwfTo0aGCMkP/wg9lVioiIi1AIFxHXYrHAffdBWhr85z/GYs38fHj9dbjhBoiNNeaQi4iIVCGFcBFxXdreUERETKIQLiJydnvDn36CZ56BgABja8MOHeCWW2D5cigsNLtKERGpQRTCRUTOOru94Z498PzzUKdOyfaGzZoZU1Zyc82uUkREagCFcBGRP9P2hiIiUsUUwkVEynLu9oZLlmh7QxERqTQK4SIi5fHwgLg4bW8oIiKVRiFcRKSitL2hiIhUEoVwEZFLoe0NRUTkMiiEi4hcjrPbG/74o7Y3FBGRClMIFxGpDKGh2t5QREQqTCFcRKQy/Xl7wwYNtL2hiIicRyFcRKQqnN3e8Pvvtb2hiIicRyFcRKQqaXtDEREphUK4iIgjaHtDERE5h0K4iIijVXR7w7Q08PWlWfPmxvSWtDSzKxcRkUqiEC4iYpYLbW/YtKkxcn52R5XcXOjSRUFcRKSGUAgXETFbadsbfvedMV3lXKdOQXS0OTWKiEilUggXEXEW525vWJbcXOMAoN9+c1xdIiJS6TzMLkBERP7E1xd8fMo+3KdnT3BzM+aWd+pkXLfcYswtFxGRakEj4SIizmjtWvDzs2/z8YH+/aF9eyOEZ2TAxIlwxx3GFJbYWGOO+S+/mFKyiIhUnEbCRUScUVQUrF5tzAHPzTUC+Nq1RjsYe42npcHHHxvXjz8aO6wsW2Z8v3lzY2Fnp07Qrp0xui4iIk5DIVxExFlFRcHp02RnZ9OsWTP77wUFwUMPGRcYB/6cDeT//rex/eGOHZCYaAT4v/61ZOpKs2bGvuUiImIahXARkZrgL38xrsGDjV1VvviiJJRv3VryGozdWM4G8g4djAWhIiLiUJoTLiJS03h5wV13wbRp8PXX8OuvkJwMffoYc8d/+cWYOx4bCyEhxpzyiRONOeaFhWZXLyLiEhTCRURququvhocfhsWLjUCemQlTpxpTVNzc4D//gUmT4M47jVDesyf885+wd6/ZlYuI1FiajiIi4krc3KB1a+MaMwZycuwXeO7aZexDvny5cX/z5iVTV9q31wJPEZFKohAuIuLKAgPhwQeNC4wQXtoCz5dfNhZ4tm9fEsqbN9cCTxGRS6TpKCIiUqJxY3jySfjgAzh6FNavN0bMW7c2tkr85BN45hm48UYICzP2LU9NhWPHzK5cRKRaUQgXEZHSeXkZ88anTjXmkZ9d4Pnww3DVVcYCzzfegF69jAWft98OEyYYO7OcOWN29SIiTk0hXEREKubsAs/kZDhwwNh5Zdo0YycWd3fYvBn+8Q9o29YI5TExsGAB7NljduUiIk5Hc8JFROTiublBq1bGNXo0WK32Czx/+AFWrDAuMA4IOneBp5+fufWLiJhMIVxERC5fQAA88IBxAfz4o/0Cz+xs45o1C7y97Rd4tmihBZ4i4nI0HUVERCpfo0YwaBCsXGks8NywAcaOhTZtIC8PPv0URoyAm26C+vWhXz94913jXhERF6AQLiIiVcvT0xj5njIFvvoKDh2Cd96Bvn2Neeb79sGiRdC7tzGX/LbbYPx42LTJfoFnWhr4+tKseXNjv/K0NPOeSUTkMmk6ioiIOFadOhAfb1xFRbB9e8nUlfR02LLFuCZPhiuugHvugQYNYN48Y5tEMP7s0gVWr4aoKFMfR0TkUiiEi4iIedzcoGVL4xo1yljguX59SSj//nt4773Sf/bUKWNO+caNxp7l11xjvJ+ISDWgEC4iIs4jIMAY4e7Sxfj6p5+MMD5oUOn3FxTAHXcYrz09oV49I5CfverXt/86KMgxzyEiUg6FcBERcV4NG8LAgTB8eMlUlHOd3Spx715jrvnPPxtXWYKCyg7o9esbId7Lq6qeRkSkmEK4iIg4v7VrjdHxU6dK2vz87OeEnz5tnOK5Z48RyvfsOf/1iRPw3/8aV2ksFrj22tID+tnXISHaUlFELptCuIiIOL+oKCNwR0cbI+I+PucvyvT1heuvN67S2Gxw7FjZAX3PHti/v+TavLn09/HxsQ/lpQV2HUYkIuVQCBcRkeohKgpOnyY7O5tmzZpd/M9bLHDllcbVsmXp95w5YwTw0gL62a9/+81YMPr992V/1pVXlh3Qw8KM0XZ394t/BhGpMRTCRUREzvLwKAnMZbFayw7oZ18fPWpcW7eW/h7u7hAaeuER9SuuKHvaS1oaREfT7Oy/Cqxdq60aRaoZh4bwrl27EhgYCEBoaCgDBw5k9OjRWCwWrr/+eiZMmICbmxupqamkpKTg4eHBoEGDiIqKIjc3l5EjR3L06FH8/f2ZPn06tWvXZtu2bUyZMgV3d3ciIyMZMmSIIx9JRERcTUAANGtmXKUpKoLDh8sO6Hv2wK+/wu7dxnWhzyltFP3oUeP0Ue2ZLlKtOSyE5+XlAZCcnFzcNnDgQIYNG8Ztt93G+PHjWbduHS1btiQ5OZkVK1aQl5dHfHw8bdu2ZenSpTRp0oSEhATWrFlDUlIS48aNY8KECcyZM4f69evzxBNPkJWVRYsWLRz1WCIiIvbc3IyTQK++Gm65pfR78vKMRaQXmp9utcKOHcZVnlOnoGNH41TSsyPsoaHGbi/e3pX7fCJSKRwWwnfu3Mnp06fp168fZ86c4emnnyYrK4tbb70VgPbt27Np0ybc3Nxo1aoVXl5eeHl5ERYWxs6dO8nMzOTxxx8vvjcpKQmr1Up+fj5hf/yzYWRkJBkZGQrhIiLi3Ly9oXFj4yqNzQbHj5ce0JcsKf1nCgth9Ojz2+vUMQL5ueH83KtePS0kFTGBw0K4j48P/fv3p2fPnvz8888MGDAAm82G5Y/5bv7+/uTk5GC1WounrJxtt1qtdu3n3hsQEGB37969e8utJT8/n+zs7Ep+wvLl5uaa8rnOSv1hT/1RQn1hT/1hz6X6w9PzvLB+w4oVuP3xr8vnsnl4cOzhh/E4eBDPgwfx+PVXPA8dwnL4sDE9pqz56cCZ4GDOXH01Bddcc/6f11xDwdVXY6sGQd2lfjfKob6w54z94bAQ3rBhQ6677josFgsNGzYkODiYrKys4u+fPHmSoKAgAgICOHnypF17YGCgXfuF7g2qwGloXl5el7ay/jJd8or+Gkr9YU/9UUJ9YU/9Yc/l++PDD0vdM92yejVX/nlOeFERHDxoTH3587V3b/Frj99/x+P33/H53//K/tzg4AuPqIeGmn4iqcv/bpxDfWHPGfvDYSF8+fLlfPfdd0ycOJGDBw9itVpp27Ytmzdv5rbbbmPjxo3cfvvthIeHM2vWLPLy8sjPz2fXrl00adKE1q1bs2HDBsLDw9m4cSNt2rQhICAAT09P9uzZQ/369UlPT9fCTBERqdkqsmf6WW5uxnaI115b9vz0oiI4cqTUcG53/f67cZV10BFAYGDZAf1s+4V2fRFxIQ4L4TExMYwZM4a4uDgsFgtTp06lVq1aPPfccyQmJtKoUSM6deqEu7s7ffv2JT4+HpvNxvDhw/H29iYuLo5Ro0YRFxeHp6cnM2fOBGDSpEmMGDGCwsJCIiMjufnmmx31SCIiIua43D3Tz+XmBlddZVytW5d+j81m7MpyoRH1vXshJ6f8xaT+/qWH83Ov2rUV1KXGc1gI9/LyKg7O51q8ePF5bbGxscTGxtq1+fr6Mnv27PPubdmyJampqZVXqIiIiNizWCAkxLjKOujIZjNGyi80mr53r7Hry//+Z1xl8fUtfTT93NAeElIS1LVvulRDOqxHRERELp/FArVqGddNN5V93/HjF5yfzi+/GPeUdyqpt7exs0tAAGRlGbvDgDFF5777YOJEaNfOmKd+xRXGn4GBxoFMIk5Av4kiIiLiOFdcYVwX2k44Jwf27bvwiPpvv8GPP5b+8/n5xoFGpfHzMwL52etsQP/zdaH2wEBj5xqRy6AQLiIiIs4lMBCaNjWuspw8aQT1G24o+54774QTJ+yvU6eM69dfL69GX9+LC+6ltQcFgZfX5dXxZ5qaU20ohIuIiEj14+8PTZoYQTM39/zv+/jApk32bTabEd7/HMzPXsePV7z99GnjOnjw8p7Dx+fig3tp3/P2NgJ4ly4l/ZGba3xd1u45YiqFcBEREam+1q4tdd90Vq8+/16LxZhDHhAAdete+mfabEYALyu0VzTQHz9uBOXcXDh06NLrAWNEPT///PZTp6BjRxgxovxwHxRk/KVAO9M4hEK4iIiIVF8Xs296ZbFYjKDv52fswX6pbDaj5osdhf/z944fLz2An1VYCNOnV6wmD4+KjcaXNzrv56cwXw6FcBEREaneKnPfdEeyWIy55b6+cPXVl/4+Nhvk5Rmnmublnf99T0+YNKliIT8vD44dM67L4eZ2cdNpyroCAoz3ulROPEdeIVxERESkOrNYjID54YdlT82paPDMyzN2p7nYUfnSFsCePWX1cp8tMPDSRuN37oQhQ5x2jrxCuIiIiEhNUBlTc7y9jSsk5PJqKSgoO8xfTLi3WkteV4ZTp4z+OX26ct7vMiiEi4iIiNQUzjI1x9MTatc2rstRWGgfxC9mND4jo/T3LG03HRMohIuIiIiIc3J3Lzng6WL5+pa9faUTuIyZ7iIiIiIiTmrtWmNO/Ln8/Ix2J6AQLiIiIiI1z9k58mdHvh2xfeVF0HQUEREREamZnGWOfCk0Ei4iIiIi4mAK4SIiIiIiDqYQLiIiIiLiYArhIiIiIiIOphAuIiIiIuJgCuEiIiIiIg6mEC4iIiIi4mAK4SIiIiIiDqYQLiIiIiLiYArhIiIiIiIO5pLH1u/bt4/u3bubXYaIiIiI1HD79u0rtd1is9lsDq5FRERERMSlaTqKiIiIiIiDKYSLiIiIiDiYQriIiIiIiIMphIuIiIiIOJhCuIiIiIiIg7nkFoVm+eabb5gxYwbJyclml2KqgoICxo4dy759+8jPz2fQoEHcc889ZpdlisLCQsaNG8dPP/2Eu7s706ZNIywszOyyTHf06FG6d+/OG2+8QePGjc0ux1Rdu3YlMDAQgNDQUKZNm2ZyReZ57bXX+Pe//01BQQFxcXH07NnT7JJM89577/H+++8DkJeXR3Z2Nps2bSIoKMjkyhyvoKCA0aNHs2/fPtzc3Jg8ebJL/38jPz+fMWPGsHfvXgICAhg/fjwNGjQwuyxTnJu7du/ezejRo7FYLFx//fVMmDABNzdzx6IVwh1kwYIFrFq1Cl9fX7NLMd2qVasIDg7mpZde4rfffqNbt24uG8LT0tIASElJYfPmzUybNo158+aZXJW5CgoKGD9+PD4+PmaXYrq8vDwAl/+LO8DmzZvZunUrS5cu5fTp07zxxhtml2Sq7t27F593MWnSJHr06OGSARxgw4YNnDlzhpSUFDZt2sSsWbOYM2eO2WWZJjU1FT8/P1JTU/nxxx+ZPHkyCxcuNLssh/tz7po2bRrDhg3jtttuY/z48axbt46OHTuaWqOmozhIWFiYS/9P4Vz33XcfTz31VPHX7u7uJlZjrg4dOjB58mQA9u/fT0hIiMkVmW/69On07t2bq666yuxSTLdz505Onz5Nv379eOSRR9i2bZvZJZkmPT2dJk2aMHjwYAYOHMhdd91ldklO4dtvv+WHH36gV69eZpdimoYNG1JYWEhRURFWqxUPD9ceX/zhhx9o3749AI0aNWLXrl0mV2SOP+eurKwsbr31VgDat2/PF198YVZpxVz7N9WBOnXqxC+//GJ2GU7B398fAKvVytChQxk2bJi5BZnMw8ODUaNG8emnnzJ79myzyzHVe++9R+3atWnXrh2vv/662eWYzsfHh/79+9OzZ09+/vlnBgwYwEcffeSSIeO3335j//79zJ8/n19++YVBgwbx0UcfYbFYzC7NVK+99hqDBw82uwxT+fn5sW/fPjp37sxvv/3G/PnzzS7JVM2aNSMtLY0OHTrwzTffcPDgQQoLC11uwOvPuctmsxX//8Lf35+cnByzSiumkXAxxYEDB3jkkUd46KGHeOCBB8wux3TTp0/n448/5rnnnuPUqVNml2OaFStW8MUXX9C3b1+ys7MZNWoUhw8fNrss0zRs2JAHH3wQi8VCw4YNCQ4Odtn+CA4OJjIyEi8vLxo1aoS3tzfHjh0zuyxTnThxgh9//JHbb7/d7FJM9eabbxIZGcnHH3/MBx98wOjRo4uncrmiHj16EBAQwCOPPEJaWhotWrRwuQBemnPnf588edIppm8phIvDHTlyhH79+jFy5EhiYmLMLsdUK1eu5LXXXgPA19cXi8Xi0v+zfOedd1i8eDHJyck0a9aM6dOnU6dOHbPLMs3y5ct54YUXADh48CBWq9Vl+6NNmzZ8/vnn2Gw2Dh48yOnTpwkODja7LFN9+eWX3HnnnWaXYbqgoKDixctXXHEFZ86cobCw0OSqzPPtt9/Spk0bkpOT6dChA/Xr1ze7JKfQvHlzNm/eDMDGjRuJiIgwuSJNRxETzJ8/nxMnTpCUlERSUhJgLKBwxYV49957L2PGjKFPnz6cOXOGsWPH4u3tbXZZ4iRiYmIYM2YMcXFxWCwWpk6d6pJTUQCioqL48ssviYmJwWazMX78eJf+CyvATz/9RGhoqNllmO7RRx9l7NixxMfHU1BQwPDhw/Hz8zO7LNNcd911vPLKK7zxxhsEBgYyZcoUs0tyCqNGjeK5554jMTGRRo0a0alTJ7NLwmKz2WxmFyEiIiIi4ko0HUVERERExMEUwkVEREREHEwhXERERETEwRTCRUREREQcTCFcRERERMTBFMJFRFzA5s2bGT58ePHXH330EV26dGH//v3FbcuXL+fvf/+73c9lZ2cTFxdX6nvOmTOHpUuXVk3BIiI1nEK4iIiLWbNmDa+//jpvvvkmdevWLW6///77ycjIsDu1dfny5fTq1cuMMkVEajSFcBERF7Jy5UoWLVrEokWLCAkJsfuer68vd999N5988gkA+fn5bNy4kfvuu4+ZM2fy2GOPERsby5gxY+x+7s+j7G3btgXgwIEDPP744/Tt25fHH3+cAwcOVPHTiYhUHwrhIiIu4quvviI1NZXjx4+Xeax3bGwsH3zwAQCfffYZf/3rXzlz5gxBQUEsWrSIlJQUtm3bxsGDB8v9vOnTp9O3b1+Sk5Pp378/M2bMqNTnERGpzlzz/GMRERdUp04dFi1axLJlyxg5ciQLFizAzc1+LKZFixacOHGCgwcP8t577zFq1Ci8vb05duwYTz/9NH5+fpw6dYqCgoIyP+fsQczfffcdr732Gv/85z+x2Wx4enpW6fOJiFQnCuEiIi7iuuuuw9vbm4cffpj09HTmzZvH4MGDz7svJiaG5ORkcnNzuf7661m3bh0HDhxg1qxZHDt2jE8//bQ4aAN4e3tz+PBhAPbt28fx48cBaNSoEf369aN169bs2rWLL7/80jEPKiJSDSiEi4i4oKlTp9K1a1fatGnD7bffbve9Bx54gLvuuotnn30WgPDwcJKSkoiNjcXLy4v69etz6NCh4vtvvPFGAgMD6dmzJ40bNyY0NBSAUaNGMXHiRPLy8sjNzS1+PxERAYvt3OEMERERERGpclqYKSIiIiLiYArhIiIiIiIOphAuIiIiIuJgCuEiIiIiIg6mEC4iIiIi4mAK4SIiIiIiDqYQLiIiIiLiYArhIiIiIiIO9v9659NwjE1kfgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "Within_Cluster_Sum_of_Square = []\n",
    "for k in range(1,11):\n",
    "    kmeans = KMeans(n_clusters = k, init = \"k-means++\")\n",
    "    kmeans.fit(data)\n",
    "    Within_Cluster_Sum_of_Square.append(kmeans.inertia_)\n",
    "plt.figure(figsize = (12, 6))\n",
    "plt.grid()\n",
    "plt.plot(range(1, 11), Within_Cluster_Sum_of_Square, linewidth = 2, color = \"red\", marker = \"8\")\n",
    "plt.xlabel(\"K Value\")\n",
    "plt.xticks(np.arange(1, 11, 1))\n",
    "plt.ylabel(\"Within_Cluster_Sum_of_Square\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "4ca45940",
   "metadata": {},
   "outputs": [],
   "source": [
    "km = KMeans(n_clusters = 4, n_init = 5)\n",
    "clusters = km.fit_predict(data)\n",
    "data[\"label\"] = clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "ef839330",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(20,10))\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.scatter(data[\"Gender\"][data.label == 0], data[\"Annual Income (k$)\"][data.label == 0], data[\"Spending Score (1-100)\"][data.label == 0], c='blue', s=60)\n",
    "ax.scatter(data[\"Gender\"][data.label == 1], data[\"Annual Income (k$)\"][data.label == 1], data[\"Spending Score (1-100)\"][data.label == 1], c='red', s=60)\n",
    "ax.scatter(data[\"Gender\"][data.label == 2], data[\"Annual Income (k$)\"][data.label == 2], data[\"Spending Score (1-100)\"][data.label == 2], c='green', s=60)\n",
    "ax.scatter(data[\"Gender\"][data.label == 3], data[\"Annual Income (k$)\"][data.label == 3], data[\"Spending Score (1-100)\"][data.label == 3], c='purple', s=60)\n",
    "\n",
    "ax.view_init(30, 185)\n",
    "plt.xlabel(\"Gender\")\n",
    "plt.ylabel(\"Annual Income (k$)\")\n",
    "ax.set_zlabel('Spending Score (1-100)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "f7bd65fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>70</td>\n",
       "      <td>29</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>71</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>71</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>1</td>\n",
       "      <td>47</td>\n",
       "      <td>71</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>72</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>73</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>74</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>0</td>\n",
       "      <td>57</td>\n",
       "      <td>75</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>76</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>77</td>\n",
       "      <td>12</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>1</td>\n",
       "      <td>48</td>\n",
       "      <td>77</td>\n",
       "      <td>36</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>78</td>\n",
       "      <td>22</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>1</td>\n",
       "      <td>43</td>\n",
       "      <td>78</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>78</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>78</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>78</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>0</td>\n",
       "      <td>56</td>\n",
       "      <td>79</td>\n",
       "      <td>35</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>81</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>85</td>\n",
       "      <td>26</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>1</td>\n",
       "      <td>42</td>\n",
       "      <td>86</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>0</td>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "      <td>27</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>87</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>1</td>\n",
       "      <td>36</td>\n",
       "      <td>87</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>0</td>\n",
       "      <td>52</td>\n",
       "      <td>88</td>\n",
       "      <td>13</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>1</td>\n",
       "      <td>58</td>\n",
       "      <td>88</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>1</td>\n",
       "      <td>59</td>\n",
       "      <td>93</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>97</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>98</td>\n",
       "      <td>15</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>99</td>\n",
       "      <td>39</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>0</td>\n",
       "      <td>54</td>\n",
       "      <td>101</td>\n",
       "      <td>24</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>103</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>103</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>113</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>0</td>\n",
       "      <td>47</td>\n",
       "      <td>120</td>\n",
       "      <td>16</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>126</td>\n",
       "      <td>28</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>1</td>\n",
       "      <td>32</td>\n",
       "      <td>137</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Gender  Age  Annual Income (k$)  Spending Score (1-100)  label\n",
       "124       0   23                  70                      29      1\n",
       "126       1   43                  71                      35      1\n",
       "128       1   59                  71                      11      1\n",
       "130       1   47                  71                       9      1\n",
       "132       0   25                  72                      34      1\n",
       "134       1   20                  73                       5      1\n",
       "136       0   44                  73                       7      1\n",
       "138       1   19                  74                      10      1\n",
       "140       0   57                  75                       5      1\n",
       "142       0   28                  76                      40      1\n",
       "144       1   25                  77                      12      1\n",
       "146       1   48                  77                      36      1\n",
       "148       0   34                  78                      22      1\n",
       "150       1   43                  78                      17      1\n",
       "152       0   44                  78                      20      1\n",
       "154       0   47                  78                      16      1\n",
       "156       1   37                  78                       1      1\n",
       "158       1   34                  78                       1      1\n",
       "160       0   56                  79                      35      1\n",
       "162       1   19                  81                       5      1\n",
       "164       1   50                  85                      26      1\n",
       "166       1   42                  86                      20      1\n",
       "168       0   36                  87                      27      1\n",
       "170       1   40                  87                      13      1\n",
       "172       1   36                  87                      10      1\n",
       "174       0   52                  88                      13      1\n",
       "176       1   58                  88                      15      1\n",
       "178       1   59                  93                      14      1\n",
       "180       0   37                  97                      32      1\n",
       "182       1   46                  98                      15      1\n",
       "184       0   41                  99                      39      1\n",
       "186       0   54                 101                      24      1\n",
       "188       0   41                 103                      17      1\n",
       "190       0   34                 103                      23      1\n",
       "192       1   33                 113                       8      1\n",
       "194       0   47                 120                      16      1\n",
       "196       0   45                 126                      28      1\n",
       "198       1   32                 137                      18      1"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.label == 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ddd1504a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Annual Income (k$)</th>\n",
       "      <th>Spending Score (1-100)</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>21</td>\n",
       "      <td>15</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>16</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>17</td>\n",
       "      <td>76</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>18</td>\n",
       "      <td>94</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>19</td>\n",
       "      <td>72</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>19</td>\n",
       "      <td>99</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>20</td>\n",
       "      <td>77</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1</td>\n",
       "      <td>22</td>\n",
       "      <td>20</td>\n",
       "      <td>79</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
       "      <td>66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>23</td>\n",
       "      <td>98</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1</td>\n",
       "      <td>31</td>\n",
       "      <td>25</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1</td>\n",
       "      <td>29</td>\n",
       "      <td>28</td>\n",
       "      <td>82</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1</td>\n",
       "      <td>35</td>\n",
       "      <td>28</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "      <td>29</td>\n",
       "      <td>87</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>30</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>33</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0</td>\n",
       "      <td>21</td>\n",
       "      <td>33</td>\n",
       "      <td>81</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0</td>\n",
       "      <td>30</td>\n",
       "      <td>34</td>\n",
       "      <td>73</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0</td>\n",
       "      <td>20</td>\n",
       "      <td>37</td>\n",
       "      <td>75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>38</td>\n",
       "      <td>92</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>39</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0</td>\n",
       "      <td>24</td>\n",
       "      <td>39</td>\n",
       "      <td>65</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1</td>\n",
       "      <td>33</td>\n",
       "      <td>42</td>\n",
       "      <td>60</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>46</td>\n",
       "      <td>55</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "      <td>48</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>1</td>\n",
       "      <td>19</td>\n",
       "      <td>48</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Gender  Age  Annual Income (k$)  Spending Score (1-100)  label\n",
       "0        1   19                  15                      39      0\n",
       "1        1   21                  15                      81      0\n",
       "3        0   23                  16                      77      0\n",
       "5        0   22                  17                      76      0\n",
       "7        0   23                  18                      94      0\n",
       "9        0   30                  19                      72      0\n",
       "11       0   35                  19                      99      0\n",
       "13       0   24                  20                      77      0\n",
       "15       1   22                  20                      79      0\n",
       "17       1   20                  21                      66      0\n",
       "19       0   35                  23                      98      0\n",
       "21       1   25                  24                      73      0\n",
       "23       1   31                  25                      73      0\n",
       "25       1   29                  28                      82      0\n",
       "27       1   35                  28                      61      0\n",
       "29       0   23                  29                      87      0\n",
       "31       0   21                  30                      73      0\n",
       "33       1   18                  33                      92      0\n",
       "35       0   21                  33                      81      0\n",
       "37       0   30                  34                      73      0\n",
       "39       0   20                  37                      75      0\n",
       "41       1   24                  38                      92      0\n",
       "43       0   31                  39                      61      0\n",
       "45       0   24                  39                      65      0\n",
       "51       1   33                  42                      60      0\n",
       "61       1   19                  46                      55      0\n",
       "65       1   18                  48                      59      0\n",
       "68       1   19                  48                      59      0"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.label == 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "22a417aa",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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